ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveTo explore the clinical and phenomics characteristics of patients with phlegm-stasis binding syndrome and its accompanied patterns in stable angina pectoris （SAP） of coronary heart disease （CHD）. MethodsA multicenter cross-sectional study design was adopted. A total of 300 patients with SAP of CHD were enrolled and classified into 120 cases of phlegm-stasis binding syndrome， 125 cases of qi deficiency-accompanied syndrome， 38 cases of qi stagnation-accompanied syndrome， and 17 cases of toxin accumulation-accompanied syndrome according to traditional Chinese medicine （TCM） patterns. Data of patients with different TCM patterns were collected， including general condition， TCM symptoms， blood lipids， coagulation function， immune indicators， and serum metabolomics. Metabolic pathway enrichment analysis was used to compare differences in phenomics characteristics among groups. Metabolites with variable importance in projection （VIP） ≥1 and fold change （FC） ≥2 were considered as representative differential metabolites. ResultsPatients in each TCM pattern type were most commonly in the 60-75 years age group， with a relatively high proportion of males. Regarding TCM symptoms， patients with phlegm-stasis binding syndrome most commonly presented with wiry-choppy or wiry-slippery pulse， chest pain， and chest tightness； in patients with qi deficiency-accompanied syndrome， fatigue， chest pain， and weak pulse were most common； in patients with qi stagnation-accompanied sydnrome， wiry-choppy or wiry-slippery pulse， chest pain， and symptoms that increase or decrease with emotional changes， belching， or flatulence were most common； in patients with toxin accumulation-accompanied syndrome， bitter taste in the mouth， chest tightness， irritability， restlessness or manic delirium， and dry and hard stools or foul-smelling diarrhea were most common. Comparisons among the different TCM patterns showed statistically significant differences in coagulation parameters （P＜0.05）， whereas no statistically significant difference was found in blood lipid levels and immune indicators （P＞0.05）.Metabolomics analysis suggested that disorders of glycerophosphate metabolism and valine， leucine， and isoleucine metabolism are characteristic features of phlegm-stasis binding syndrome and its accompanied patterns. The representative differential metabolites between phlegm-stasis binding syndrome and qi deficiency-accompanied syndrome were 7,8-dihydrobiopterin （FC = 3.58） and oxypurinol （FC = 124.50）. Those between phlegm-stasis binding syndrome and qi stagnation-accompanied syndrome were cytidine 5′-diphosphocholine （FC = 2.62） and D-mannosamine （FC = 2.99）. Those between phlegm-stasis binding syndrome and toxin accumulation-accompanied syndrome were anserine （FC = 7.83） and canrenone （FC = 8.94）. ConclusionThere are certain differences in the clinical characteristics and phenomics characteristics among patients with SAP due to CHD exhibiting phlegm-stasis binding syndrome and its accompanied patterns. The phenomics characteristics mainly involve biological alterations such as lipid metabolism disorders， amino acid metabolism abnormalities， and multiple immune indicators activation， which may provide a reference for precise differentiation and treatment of SAP of CHD in TCM clinical practice.

ObjectiveTo explore the clinical and phenomics characteristics of patients with phlegm-stasis binding syndrome and its accompanied patterns in stable angina pectoris （SAP） of coronary heart disease （CHD）. MethodsA multicenter cross-sectional study design was adopted. A total of 300 patients with SAP of CHD were enrolled and classified into 120 cases of phlegm-stasis binding syndrome， 125 cases of qi deficiency-accompanied syndrome， 38 cases of qi stagnation-accompanied syndrome， and 17 cases of toxin accumulation-accompanied syndrome according to traditional Chinese medicine （TCM） patterns. Data of patients with different TCM patterns were collected， including general condition， TCM symptoms， blood lipids， coagulation function， immune indicators， and serum metabolomics. Metabolic pathway enrichment analysis was used to compare differences in phenomics characteristics among groups. Metabolites with variable importance in projection （VIP） ≥1 and fold change （FC） ≥2 were considered as representative differential metabolites. ResultsPatients in each TCM pattern type were most commonly in the 60-75 years age group， with a relatively high proportion of males. Regarding TCM symptoms， patients with phlegm-stasis binding syndrome most commonly presented with wiry-choppy or wiry-slippery pulse， chest pain， and chest tightness； in patients with qi deficiency-accompanied syndrome， fatigue， chest pain， and weak pulse were most common； in patients with qi stagnation-accompanied sydnrome， wiry-choppy or wiry-slippery pulse， chest pain， and symptoms that increase or decrease with emotional changes， belching， or flatulence were most common； in patients with toxin accumulation-accompanied syndrome， bitter taste in the mouth， chest tightness， irritability， restlessness or manic delirium， and dry and hard stools or foul-smelling diarrhea were most common. Comparisons among the different TCM patterns showed statistically significant differences in coagulation parameters （P＜0.05）， whereas no statistically significant difference was found in blood lipid levels and immune indicators （P＞0.05）.Metabolomics analysis suggested that disorders of glycerophosphate metabolism and valine， leucine， and isoleucine metabolism are characteristic features of phlegm-stasis binding syndrome and its accompanied patterns. The representative differential metabolites between phlegm-stasis binding syndrome and qi deficiency-accompanied syndrome were 7,8-dihydrobiopterin （FC = 3.58） and oxypurinol （FC = 124.50）. Those between phlegm-stasis binding syndrome and qi stagnation-accompanied syndrome were cytidine 5′-diphosphocholine （FC = 2.62） and D-mannosamine （FC = 2.99）. Those between phlegm-stasis binding syndrome and toxin accumulation-accompanied syndrome were anserine （FC = 7.83） and canrenone （FC = 8.94）. ConclusionThere are certain differences in the clinical characteristics and phenomics characteristics among patients with SAP due to CHD exhibiting phlegm-stasis binding syndrome and its accompanied patterns. The phenomics characteristics mainly involve biological alterations such as lipid metabolism disorders， amino acid metabolism abnormalities， and multiple immune indicators activation， which may provide a reference for precise differentiation and treatment of SAP of CHD in TCM clinical practice.

Intervertebral disc degeneration(IDD)is a prevalent clinical degenerative disease that currently can only be treated through conservative and surgical treatments,which only alleviate symptoms and are not significantly effective.In recent years,nanoparticles have been widely studied in the biomedical field due to their biodegradability,biocompatibility,extended body circulation,sustained and controlled release,and precise drug targeting.Nanoparticle drug delivery systems have the potential to deliver a range of therapeutic agents including proteins,drugs,genes,and cells,thereby promoting tissue and cell repair and regeneration,which offers hope for IDD treatment.However,there are still challenges in translating experimental data into practical therapies applicable to humans.This review summarizes recent research progress on drug delivery systems for IDD treatment based on nanoparticles and provides insights and prospects for the challenges faced by nanoparticles,aiming to provide a reference for the clinical translation of nanoparticle-based treatment for IDD.

Objective To investigate the effects of varying durations of overwork on cardiomyocyte pyroptosis in mice.Methods A total of 24 SPF KM mice were randomly divided into four groups(n=6)using a random number table:control group,2-week overwork(W2)group,4-week overwork(W4)group,and 6-week overwork(W6)group.Mice in control group were normally raised,while those in W2,W4,and W6 groups were forced to stand in water for 8 h and then restrained for 3 h daily for 2,4,6 weeks,respectively.The general condition and weekly weight changes of the mice were observed.After modeling,blood samples were collected,and hearts were excised.Myocardial histopathological changes were assessed using hematoxylin and eosin(HE)staining.The localization of gasdermin D(GSDMD)protein in myocardial tissue was detected through immunohistochemical staining,and the expression levels of pyroptosis-related proteins[NOD-like protein receptor 3(NLRP3),Caspase-1,GSDMD]in myocardial tissue were analyzed using Western blotting.The contents of interleukin-1β(IL-1β)and interleukin-18(IL-18)in serum and myocardial tissues were measured using ELISA.Results(1)The weight of control group mice increased steadily within 2 weeks.In W2 group,there was no significant weight change within 2 weeks,while in W4 and W6 groups,the body weights were higher than their initial values from the 2nd to 6th week.Compared with control group,the body weights of W2,W4,and W6 groups were lower than those of control group in the 1st and 2nd week,with statistically significant differences(P<0.05).The activity levels of the mice in W2,W4,and W6 groups initially increased and then decreased,with their fur becoming dull and falling out,and their mental state deteriorating.(2)In control group,cardiomyocytes were neatly arranged,and the nuclear morphology was normal.Compared with control group,in W2 group,cardiomyocyte arrangement was less regular,and capillary congestion was increased.In W4 group,the vascular congestion in the myocardium was significantly increased,the interstitial tissue was hyperplastic,and vacuolization appeared around the nuclei.In W6 group,the myocardial interstitium was loose,fat infiltration was increased,vacuolization around the nuclei was increased,and myocardial fibers were swollen,and the arrangement was disordered.(3)GSDMD was mainly located in the cytoplasm of cardiomyocytes.Compared with control group,the expression levels of NLRP3,Caspase-1,and GSDMD proteins in W2,W4,and W6 groups were significantly increased,and the expression levels were in the order of W6 group>W4 group>W2 group,with significant differences(P<0.05).(4)Compared to control group,the levels of IL-1β in serum and myocardial tissues of W2,W4,and W6 groups were significantly increased.In serum,the level of IL-1β in W6 group was higher than those in W2 and W4 groups,and in myocardial tissue,the levels in W4 and W6 groups were higher than those in the W2 group,with significant differences(P<0.05).There were no significant differences in IL-1β levels in serum among W2 and W4 groups,nor were there significant differences in myocardial tissue between W4 and W6 groups(P>0.05).Compared with control group,the levels of IL-18 in serum and myocardial tissue of W4 and W6 groups were significantly increased(P<0.05).In serum,the levels of IL-18 in W4 and W6 groups were higher than that in W2 group,and in myocardial tissue,the level in W6 group was higher than those in W2 and W4 groups,with the differences being statistically significant(P<0.05).Conclusions Overwork can cause structural damage to mouse myocardial tissue,increase the expression of pyroptosis proteins NLRP3,Caspase-1,GSDMD,and aggravate myocardial inflammatory responses in overworked mice.Cardiomyocyte pyroptosis may be one of the factors contributing to sudden cardiac death induced by overwork.

Breast cancer(BC)is one of the most prevalent malignant tumors affecting women worldwide,with its incidence rate continuously increasing.As a result,treatment strategies for this disease have received considerable attention.Research has highlighted the crucial role of the Hedgehog(Hh)signaling pathway in the initiation and progression of BC,particularly in promoting tumor growth and metastasis.There-fore,molecular targets within this pathway represent promising opportunities for the development of novel BC therapies.This study aims to elucidate the therapeutic mechanisms by which natural com-pounds modulate the Hh signaling pathway in BC.By conducting a comprehensive review of various natural compounds,including polyphenols,terpenes,and alkaloids,we reveal both common and unique regulatory mechanisms that influence this pathway.This investigation represents the first comprehen-sive analysis of five distinct mechanisms through which natural compounds modulate key molecules within the Hh pathway and their impact on the aggressive behaviors of BC.Furthermore,by exploring the structure-activity relationships between these compounds and their molecular targets,we shed light on the specific structural features that enable natural compounds to interact with various components of the Hh pathway.These novel insights contribute to advancing the development and clinical application of natural compound-based therapeutics.Our thorough review not only lays the groundwork for exploring innovative BC treatments but also opens new avenues for leveraging natural compounds in cancer therapy.

A strategy combining a tailored database and high-throughput activity screening that discover bioactive metabolites derived from Magnoliae Officinalis Cortex(MOC)was developed and implemented to rapidly profile and discover bioactive metabolites in vivo derived from traditional Chinese medicine(TCM).The strategy possessed four characteristics:1)The tailored database consisted of metabolites derived from big data-originated reference compound,metabolites predicted in silico,and MOC chemical profile-based pseudomolecular ions.2)When profiling MOC-derived metabolites in vivo,attentions were paid not only to prototypes of MOC compounds and metabolites directly derived from MOC compounds,as reported by most papers,but also to isomerized metabolites and the degradation products of MOC compounds as well as their derived metabolites.3)Metabolite traceability was performed,especially to distinguish isomeric prototypes-derived metabolites,prototypes of MOC compounds as well as phase Ⅰ metabolites derived from other MOC compounds.4)Molecular docking was utilized for high-throughput activity screening and molecular dynamic simulation as well as zebrafish model were used for verification.Using this strategy,134 metabolites were swiftly characterized after the oral administration of MOC to rats,and several metabolites were reported for the first time.Furthermore,17 potential active metabolites were discovered by targeting the motilin,dopamine D2,and the serotonin type 4(5-HT4)receptors,and part bioactivities were verified using molecular dynamic simulation and a zebrafish constipation model.This study extends the application of mass spectrometry(MS)to rapidly profile TCM-derived metabolites in vivo,which will help pharmacologists rapidly discover potent metabolites from a complex matrix.

Objective This study investigated feasible cases and their significance in promoting the"generalized"development of inspection through digital-intelligent equipment.Methods A qualitative research approach was used,involving interviews conducted between February 2025 and March 2025 with experts in traditional Chinese medicine diagnostics,clinical research methodology,medical engineering integration,and related disciplines,using both online and offline methods.In accordance with the Consolidated Criteria for Reporting Qualitative Research,feasible cases involving the specific application of digital equipment in various parts of observation were collected through item enrichment.The significance of extending observation capabilities via these cases was analyzed,along with the overall implications of integrating digital technologies with traditional inspection method.Results Interviews were completed with 11 experts from domestic universities and research institutes in the fields of traditional Chinese medicine diagnosis,medical engineering integration,and related disciplines.A total of 78 feasible cases of digital-intelligent inspection were identified,along with 69 insights regarding the significance of enhancing the inspection capabilities.These insights were synthesized into two dimensions and 23 holistic meanings.The first dimension is to expand the scope of inspection,including obtaining internal environmental characteristics,observing external environmental characteristics,expanding thermodynamic characteristic data,and crossing time and space.The second dimension is to improve the quality of observation and diagnosis information collection and analysis,including 19 specific meanings,such as standardized collection environment,objective quantification,and refined observation.Conclusion Digital-intelligent equipment plays a significant role in expanding the scope of inspection content and achieving high-quality acquisition and analysis of extensive inspection information.These advancements extend and enrich the capabilities of traditional inspection method in traditional Chinese medicine.